Dave Wells is an advisory consultant, educator, and industry analyst dedicated to building meaningful connections throughout the path from data to business value. More than forty years of information systems experience combined with over ten years of business management give him a unique perspective about the connections among business, information, data, and technology.

Managing data in an analytics- driven organization is complex and challenging. Abundant data sources, variety of data types, and multiple use cases result in many data pipelines—possibly as many as one distinct pipeline for each use case. Capabilities to find data, manage dataflow and workflow, and deliver the right data in the right forms for analysis are essential for all who seek to become analytics-driven organizations.

Multiple and complex data pipelines quickly become chaotic with pressures of agile, democratization, self-service, and organizational “pockets” of analytics. Increased difficulty of governance and uncertainty of data usage are only the beginning. From enterprise BI to self-service analysis, data pipeline management should ensure that data analysis results are traceable, reproducible, and of production strength. Robust pipeline management works across a variety of platforms from relational to Hadoop, and recognizes today’s bi-directional data flows where any data store may function in both source and target roles.

You Will Learn:

•The challenges and complexities of modern data pipelines

•Why dataflow and workflow are critical parts of analytics architecture and how they fit into architecture

•The roles and functions of metadata in pipeline management

•The important relationships of pipeline management and data governance